3 papers
cs.CV2026
CRAFT: Continuous Reasoning and Agentic Feedback Tuning for Multimodal Text-to-Image Generation
V. Kovalev, A. Kuvshinov, A. Buzovkin +2
Recent work has shown that inference-time reasoning and reflection can improve text-to-image generation without retraining. However, existing approaches often rely on implicit, hol…
cs.CL2025
Investigating the Robustness of Retrieval-Augmented Generation at the Query Level
Sezen Perçin, Xin Su, Qutub Sha Syed +4
Large language models (LLMs) are very costly and inefficient to update with new information. To address this limitation, retrieval-augmented generation (RAG) has been proposed as a…
cs.CL2024
Extracting Unlearned Information from LLMs with Activation Steering
Atakan SeyitoÄlu, Aleksei Kuvshinov, Leo Schwinn +1
An unintended consequence of the vast pretraining of Large Language Models (LLMs) is the verbatim memorization of fragments of their training data, which may contain sensitive or c…